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Peer reviewed Peer reviewed
Margulis, Eugene L. – Information Processing and Management, 1993
Reports on the validity of the Multiple Poisson (nP) model of word distribution in full-text document collections. A practical algorithm for determining whether a certain word is distributed according to an nP distribution and the results of a test of this algorithm in three different document collections are described. (14 references) (KRN)
Descriptors: Algorithms, Full Text Databases, Graphs, Information Retrieval
Peer reviewed Peer reviewed
Willett, Peter – Information Processing and Management, 1985
Reports algorithm for calculation of term discrimination values that is sufficiently fast in operation to permit use of exact values. Evidence is presented to show that relationship between term discrimination and term frequency is crucially dependent upon type of inter-document similarity measure used for calculation of discrimination values. (13…
Descriptors: Algorithms, Graphs, Information Retrieval, Information Systems
Peer reviewed Peer reviewed
Kraft, Donald H.; Waller, W. G. – Information Processing and Management, 1981
Presents a dynamic model of user behavior when scanning an information storage and retrieval system output list, compares rules for determining the user's optimum stopping point, presents an algorithm for implementing the Bayesian model, and discusses implications for retrieval system design. Provided are 13 figures and 15 references. (Author/RBF)
Descriptors: Algorithms, Bayesian Statistics, Behavior Patterns, Graphs
Peer reviewed Peer reviewed
Smith, F. J.; Devine, K. – Information Processing and Management, 1985
Zipfian laws for frequency distributions of word pairs and longer phrases are derived from text sample analysis. From crossing of Zipfian curves, it is deduced that number of multi-word phrases that occur frequently in text is surprisingly small, of same order of magnitude as number of individual word-types. (8 references) (EJS)
Descriptors: Algorithms, Graphs, Indexing, Information Retrieval